Content based image retrieval in astronomy, a technique that uses visual contents to search astronomical images from a large scale image databases according to the users interests, has been an active and fast advancing research area. Early techniques were not generally based on visual features but the textual annotation of images. In other words, images were first annotated with text and then searched using a text-based approach from traditional database management systems. Comprehensive surveys of early text-based image retrieval methods can be found. Text-based image retrieval uses traditional database techniques to manage images. Through text descriptions, images can be organized by topical or semantic hierarchies to facilitate easy navigation and browsing based on standard Boolean queries. The aim of this paper is to review the current state of the art in content-based image retrieval in astronomical images, a technique for retrieving astronomical images on the basis of color distributions. The paper highlights the various retrieval methods like color histogram, color coherence vector and multi scale color coherence vector. The findings are based on both review of the relevant literature and discussions with researchers and practitioners in this field.

AbstractThe paper focuses on parallelization of queries execution on a shared memory parallel database system. In this paper, a new data structures, named Warp edged Bushy trees, is proposed for facilitating compile time optimization. The warp edged bushy tree is a modified version of bushy trees , which provides better response time than bushy trees, during query processing.